In conventional multi-user multiple-input multiple-output (MU-MIMO) systems with frequency
division duplexing (FDD), channel acquisition and precoder optimization processes have …

Using precoding to suppress multi-user interference is a well-known technique to improve
spectra efficiency in multiuser multiple-input multiple-output (MU-MIMO) systems, and the …

We propose a versatile feedback scheme for both single-and multi-user multiple-input
multiple-output (MIMO) frequency division duplex (FDD) systems. Particularly, we propose …

In this letter, we propose a joint pilot design and channel estimation scheme based on the
deep learning (DL) technique for multiuser multiple-input multiple output (MIMO) channels …

In this paper, we propose two deep learning (DL) based receiver schemes in uplink multiple-
input multiple-output (MIMO) systems. In the first scheme, we design a pilot-assisted MIMO …

Precoding design exploiting deep learning methods has been widely studied for multiuser
multiple-input multiple-output (MU-MIMO) systems. However, conventional neural precoding …

We propose a deep learning-based channel estimation, quantization, feedback, and
precoding method for downlink multiuser multiple-input and multiple-output systems. In the …

This paper shows that deep neural network (DNN) can be used for efficient and distributed
channel estimation, quantization, feedback, and downlink multiuser precoding for a …

Hybrid computation is an important step in multiple-user mm Wave MIMO systems to reduce
complexity and expense while obtaining an acceptable sum-rate. Prior research on hybrid …

In this paper, we propose a practical downlink multiuser multiple-input-multiple-output (MU-
MIMO) system. The proposed MU-MIMO system focuses on improving two limiting factors for …